{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c4318006-0166-4f65-a62b-e2ba165baa1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1050x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "各区域销量：\n",
      "region\n",
      "华北    628\n",
      "华南    727\n",
      "东北    523\n",
      "西北    662\n",
      "西南    784\n",
      "华东    568\n",
      "Name: quantity, dtype: int64\n",
      "\n",
      "平均值： 648.6666666666666\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "基于给定 Schema，使用 Faker 生成模拟订单数据，\n",
    "并仿照 Excel 模板绘制“3月各区域销量分布”柱状图 + 平均线。\n",
    "\n",
    "依赖：\n",
    "    pip install faker pandas matplotlib\n",
    "\"\"\"\n",
    "\n",
    "from typing import List, Dict\n",
    "import random\n",
    "from datetime import datetime\n",
    "\n",
    "from faker import Faker\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# =========================\n",
    "# 1. 使用 Faker 生成模拟订单数据（参考 erp_order 结构）\n",
    "# =========================\n",
    "\n",
    "fake = Faker(\"zh_CN\")\n",
    "random.seed(42)\n",
    "\n",
    "# 生成记录数（不少于 1000）\n",
    "NUM_ROWS = 1500\n",
    "\n",
    "# 省份与大区映射（用于后续做“各区域销量”）\n",
    "region_provinces: Dict[str, List[str]] = {\n",
    "    \"华北\": [\"北京\", \"天津\", \"河北\", \"山西\", \"内蒙古\"],\n",
    "    \"华东\": [\"上海\", \"江苏\", \"浙江\", \"安徽\", \"福建\", \"江西\", \"山东\"],\n",
    "    \"华南\": [\"广东\", \"广西\", \"海南\"],\n",
    "    \"华中\": [\"河南\", \"湖北\", \"湖南\"],\n",
    "    \"东北\": [\"辽宁\", \"吉林\", \"黑龙江\"],\n",
    "    \"西北\": [\"陕西\", \"甘肃\", \"青海\", \"宁夏\", \"新疆\"],\n",
    "    \"西南\": [\"重庆\", \"四川\", \"贵州\", \"云南\", \"西藏\"],\n",
    "}\n",
    "\n",
    "province_to_region = {\n",
    "    prov: region for region, provs in region_provinces.items() for prov in provs\n",
    "}\n",
    "\n",
    "platforms = [\"天猫旗舰店\", \"抖音旗舰店\", \"京东自营\", \"小红书\", \"淘宝店铺\"]\n",
    "refund_status_choices = [\"未申请退款\", \"成功退款\", \"退款关闭\"]\n",
    "status_choices = [\"已付款\", \"已发货\", \"已完成\", \"待付款\"]\n",
    "\n",
    "rows = []\n",
    "\n",
    "# 下单时间：2022-03-01 ~ 2022-03-31\n",
    "start_dt = datetime(2022, 3, 1)\n",
    "end_dt = datetime(2022, 3, 31, 23, 59, 59)\n",
    "\n",
    "for _ in range(NUM_ROWS):\n",
    "    # 随机省份 & 大区\n",
    "    region = random.choice(list(region_provinces.keys()))\n",
    "    province = random.choice(region_provinces[region])\n",
    "    city = fake.city_name()\n",
    "\n",
    "    order_time = fake.date_time_between_dates(\n",
    "        datetime_start=start_dt,\n",
    "        datetime_end=end_dt,\n",
    "    )\n",
    "    payment_date = order_time\n",
    "    shipping_date = fake.date_time_between_dates(\n",
    "        datetime_start=order_time,\n",
    "        datetime_end=datetime(2022, 4, 5, 23, 59, 59),\n",
    "    )\n",
    "\n",
    "    quantity = random.randint(1, 5)\n",
    "    unit_price = round(random.uniform(80, 600), 2)\n",
    "    product_amount = round(quantity * unit_price, 2)\n",
    "    payable_amount = product_amount\n",
    "    # 模拟 8~10 折的优惠\n",
    "    discount_ratio = random.uniform(0.8, 1.0)\n",
    "    paid_amount = round(product_amount * discount_ratio, 2)\n",
    "\n",
    "    # 构造一行接近 erp_order 结构的记录\n",
    "    row = {\n",
    "        # 订单主信息（部分字段）\n",
    "        \"internal_order_number\": fake.uuid4(),\n",
    "        \"online_order_number\": fake.bothify(text=\"ON##########\"),\n",
    "        \"store_name\": random.choice(platforms),\n",
    "        \"full_channel_user_id\": fake.uuid4(),\n",
    "        \"shipping_date\": shipping_date,\n",
    "        \"payment_date\": payment_date,\n",
    "        \"payable_amount\": payable_amount,\n",
    "        \"paid_amount\": paid_amount,\n",
    "        \"status\": random.choice(status_choices),\n",
    "        \"consignee\": fake.name(),\n",
    "        \"spu\": f\"SPU{random.randint(1000, 9999)}\",\n",
    "        \"order_time\": order_time,\n",
    "        \"province\": province,\n",
    "        \"city\": city,\n",
    "        \"platform\": random.choice(platforms),\n",
    "        \"original_online_order_number\": fake.bothify(text=\"ON##########\"),\n",
    "\n",
    "        # 商品信息\n",
    "        \"sku\": f\"SKU{random.randint(100000, 999999)}\",\n",
    "        \"quantity\": quantity,\n",
    "        \"unit_price\": unit_price,\n",
    "        \"product_name\": fake.word(),\n",
    "        \"color_and_spec\": fake.color_name(),\n",
    "        \"product_amount\": product_amount,\n",
    "        \"original_price\": product_amount,\n",
    "        \"is_gift\": \"否\",\n",
    "        \"sub_order_status\": random.choice(status_choices),\n",
    "        \"refund_status\": random.choices(\n",
    "            refund_status_choices, weights=[0.8, 0.1, 0.1]\n",
    "        )[0],\n",
    "        \"registered_quantity\": quantity,\n",
    "        \"actual_refund_quantity\": random.choice([0, 0, 0, 1]),  # 大部分不退货\n",
    "\n",
    "        # 自加字段：大区，方便后续聚合分析\n",
    "        \"region\": region,\n",
    "    }\n",
    "    rows.append(row)\n",
    "\n",
    "df = pd.DataFrame(rows)\n",
    "\n",
    "# 如需查看模拟数据，可解开：\n",
    "# print(df.head())\n",
    "\n",
    "\n",
    "# =========================\n",
    "# 2. 统计 3 月各区域销量（以 quantity 为“销量”）\n",
    "# =========================\n",
    "\n",
    "# 只取 Excel 模板中的六个区域\n",
    "target_regions = [\"华北\", \"华南\", \"东北\", \"西北\", \"西南\", \"华东\"]\n",
    "\n",
    "region_sales = (\n",
    "    df[df[\"region\"].isin(target_regions)]\n",
    "    .groupby(\"region\")[\"quantity\"]\n",
    "    .sum()\n",
    "    .reindex(target_regions)\n",
    ")\n",
    "\n",
    "total_sales = region_sales.sum()\n",
    "region_ratio = region_sales / total_sales\n",
    "avg_sales = region_sales.mean()  # 平均值\n",
    "\n",
    "max_region = region_sales.idxmax()\n",
    "min_region = region_sales.idxmin()\n",
    "\n",
    "\n",
    "# =========================\n",
    "# 3. 参照 Excel 模板进行可视化（柱状图 + 平均线）\n",
    "# =========================\n",
    "\n",
    "# 中文字体（你本地可以改为已安装的字体，如 Microsoft YaHei）\n",
    "plt.rcParams[\"font.sans-serif\"] = [\"SimHei\"]\n",
    "plt.rcParams[\"axes.unicode_minus\"] = False\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10.5, 6))\n",
    "\n",
    "# 深蓝背景\n",
    "bg_color = \"#111b3c\"\n",
    "fig.patch.set_facecolor(bg_color)\n",
    "ax.set_facecolor(bg_color)\n",
    "\n",
    "# 柱状图（亮蓝色）\n",
    "bars = ax.bar(\n",
    "    region_sales.index,\n",
    "    region_sales.values,\n",
    "    width=0.6,\n",
    "    color=\"#008CFF\",\n",
    ")\n",
    "\n",
    "# Y 轴范围留一定余量\n",
    "y_max = (region_sales.max() // 50 + 3) * 50\n",
    "ax.set_ylim(0, y_max)\n",
    "\n",
    "# Y 轴网格线：虚线 + 浅灰色\n",
    "ax.yaxis.grid(True, linestyle=\"--\", color=\"#6b7280\", alpha=0.4)\n",
    "ax.xaxis.grid(False)\n",
    "\n",
    "# 边框处理：去掉上、右边框\n",
    "ax.spines[\"top\"].set_visible(False)\n",
    "ax.spines[\"right\"].set_visible(False)\n",
    "ax.spines[\"left\"].set_color(\"#cbd5f5\")\n",
    "ax.spines[\"bottom\"].set_color(\"#cbd5f5\")\n",
    "\n",
    "# 坐标轴刻度样式\n",
    "ax.tick_params(axis=\"x\", colors=\"white\", labelsize=11)\n",
    "ax.tick_params(axis=\"y\", colors=\"white\", labelsize=10)\n",
    "ax.set_ylabel(\"\", color=\"white\")\n",
    "\n",
    "# 每根柱子顶部标注具体数值\n",
    "for bar, value in zip(bars, region_sales.values):\n",
    "    ax.text(\n",
    "        bar.get_x() + bar.get_width() / 2,\n",
    "        bar.get_height() + y_max * 0.02,\n",
    "        f\"{int(value)}\",\n",
    "        ha=\"center\",\n",
    "        va=\"bottom\",\n",
    "        color=\"white\",\n",
    "        fontsize=11,\n",
    "    )\n",
    "\n",
    "# ------- 平均线（黄色） -------\n",
    "avg_y = avg_sales\n",
    "ax.axhline(\n",
    "    y=avg_y,\n",
    "    color=\"#FDBA21\",     # 金黄\n",
    "    linewidth=2,\n",
    ")\n",
    "\n",
    "# 平均值文字（黄色）靠右\n",
    "ax.text(\n",
    "    len(target_regions) - 0.1,\n",
    "    avg_y + y_max * 0.02,\n",
    "    f\"平均值： {int(avg_y)}\",\n",
    "    color=\"#FDBA21\",\n",
    "    fontsize=11,\n",
    "    ha=\"right\",\n",
    "    va=\"bottom\",\n",
    ")\n",
    "\n",
    "# ------- 标题 & 副标题 -------\n",
    "title_text = \"3月各区域销量分布\"\n",
    "subtitle_text = (\n",
    "    f\"{max_region}销量最多占比总销量的{region_ratio[max_region]*100:.1f}%，\"\n",
    "    f\"{min_region}销量最低\"\n",
    ")\n",
    "\n",
    "fig.text(0.06, 0.93, title_text, fontsize=22, color=\"white\", weight=\"bold\")\n",
    "fig.text(0.06, 0.87, subtitle_text, fontsize=13, color=\"white\")\n",
    "\n",
    "# ------- 底部注释 -------\n",
    "note_text = (\n",
    "    \"※ 数据由 Faker 模拟生成，仅用于可视化示例；\"\n",
    "    \"统计时间：2022-03-01 至 2022-03-31\"\n",
    ")\n",
    "fig.text(0.06, 0.05, note_text, fontsize=9, color=\"#cbd5f5\")\n",
    "\n",
    "# 调整布局，预留出标题和注释空间\n",
    "plt.tight_layout(rect=[0.03, 0.08, 0.98, 0.85])\n",
    "\n",
    "# 展示图表\n",
    "plt.show()\n",
    "\n",
    "# 如果想看一下区域销量与平均值\n",
    "print(\"各区域销量：\")\n",
    "print(region_sales)\n",
    "print(\"\\n平均值：\", avg_sales)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe875e20-f5cd-4462-8456-92c46e89bef7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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